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I'm passing a list to map and want to return a data.frame object with incorporated names.
For example:
library(tidyverse)
library(broom)
mtcars %>%
split(.$vs) %>%
map_df(~ tidy(lm(mpg ~ cyl, .)))
term estimate std.error statistic p.value
1 (Intercept) 36.926733 3.690822 10.005017 2.727754e-08
2 cyl -2.728218 0.490297 -5.564419 4.272958e-05
3 (Intercept) 41.940000 5.778467 7.257981 1.003636e-05
4 cyl -3.802500 1.240052 -3.066404 9.781943e-03
How can I extract names (vs group) within map and add them as an additional column in the result like this:
term estimate std.error statistic p.value GROUP
1 (Intercept) 36.926733 3.690822 10.005017 2.727754e-08 0
2 cyl -2.728218 0.490297 -5.564419 4.272958e-05 0
3 (Intercept) 41.940000 5.778467 7.257981 1.003636e-05 1
4 cyl -3.802500 1.240052 -3.066404 9.781943e-03 1
662
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Use the .id parameter, which map_df will pass along to dplyr::bind_rows:
library(purrr)
mtcars %>%
split(.$vs) %>%
map_dfr(~broom::tidy(lm(mpg ~ cyl, .)), .id = 'GROUP')
#> GROUP term estimate std.error statistic p.value
#> 1 0 (Intercept) 36.926733 3.690822 10.005017 2.727754e-08
#> 2 0 cyl -2.728218 0.490297 -5.564419 4.272958e-05
#> 3 1 (Intercept) 41.940000 5.778467 7.257981 1.003636e-05
#> 4 1 cyl -3.802500 1.240052 -3.066404 9.781943e-03
Here is one option with group_by/nest/unnest
mtcars %>%
group_by(GROUP = vs) %>%
nest(-GROUP) %>%
mutate(out = map(data, ~ tidy(lm(mpg ~ cyl, .x))) ) %>%
select(-data) %>%
unnest
# A tibble: 4 x 6
# GROUP term estimate std.error statistic p.value
# <dbl> <chr> <dbl> <dbl> <dbl> <dbl>
#1 0 (Intercept) 36.9 3.69 10.0 0.0000000273
#2 0 cyl - 2.73 0.490 - 5.56 0.0000427
#3 1.00 (Intercept) 41.9 5.78 7.26 0.0000100
#4 1.00 cyl - 3.80 1.24 - 3.07 0.00978
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